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Database Indexing allows us to cut down the number of rows/records that need to be examined when a select query with a where clause is executed.

When a select query with a where clause is executed, every single row is checked to see if the query match the condition. This effectively means that the entire table will have to be scanned (known as the full table scan).

Without Indexing

An index is a data structure that stores the values for a certain specific column of a table and helps us avoid a full table scan. If the table is not indexed, the query will likely not recognize that the row order is optimized, so the query should search the rows linearly. That is, the query must search every row to find a row that matches the criteria. As you can imagine, this can take a long time. Examining every row is not very efficient.

This will take more and more time as the size of the table grows. With the sophistication of data, what can eventually happen is that a table with 1 billion rows is joined with another table with 1 billion rows. The query should spend twice as much time searching twice as many rows.

How can we imporve

If the database tables are in order, we can make search more efficiently without looking up all the records. For example, we are finding a user whose age is 18. If the age column is sorted , we can skip the records of age starting from 18.

In reality, the database table does not sort itself every time the query condition changes to optimize query performance. This is unrealistic. In reality, the index creates the data structure in the database. The data structure type is very likely to be a B-tree. There are many advantages of B-trees, but the main advantage of our purpose is that they are sortable and makes the search more efficiently.

How it works

Database indexes will also store pointers which are simply reference information for the location of the additional information in memory. So to be summarized, it creates a structure with the key of indexed column and the value of pointers which reference the actual database record. When a conditional query runs, it looks up the sorted index structure according to the data structure (B-Tree in this case), get the pointers and then go for the actual records.

Index cost

There is always something you need to give back if you want something. Index also requires additional memory. The more indexes you add, the more memory will be used. Don’t forget to index only the columns that are frequently queried. Otherwise, indexing each column consumes a huge amount of memory.

Secondly, the write operation will be a bit slower as it needs to create a index each time you add an entry to the table. A similar situation applies to updating or deleting data.

I think this will give you the abstraction knowledge of what database indexing looks like.

By Yuuma

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Need an icon not in Material?

The material design offers many helpful patterns, including a great set of icons. But they are not the only icons out there. Font awesome’s icon are truly, well, iconic. Luckily, with font_awesome_flutter package, including them in our flutter app.

It’s too simple so let’s build with simple app including flutter font awesome icon.

Firstly, we need to add font_awesome_flutter package in our pubspec.yaml file.

dependencies:
  font_awesome_flutter: ^9.2.0

For use font_awesome_flutter package, we will need to import this package .

import 'package:font_awesome_flutter/font_awesome_flutter.dart';

To start the two components of Material Icons– wrapping with Icon and the inner icon_data value. Icons.menu is a default material icon. We will use this icon in our app.

Icon(Icons.menu)

To change icon size and color:

Icon(FontAwesomeIcons.user,
    size: 50, //Icon Size
    color: Colors.white, 
)

Use with FaIcon widget and let’s build a simple app then find out fond awesome icon usage!

return Scaffold(
      appBar: AppBar(
          centerTitle: true,
          leading: Icon(Icons.menu),
          title: const Text("Font Awesome Icons")
      ),
      body: Center(
        child: Column(
          mainAxisAlignment: MainAxisAlignment.center,
          children: [

            const Text(" Font Awesome Flutter package",textAlign:TextAlign.center,style: TextStyle(fontSize: 30),),
            const SizedBox(height: 20,),
            //brand Icons
            const Text("Brand Icons",textAlign: TextAlign.start,style: TextStyle(fontWeight: FontWeight.bold,fontStyle:FontStyle.italic,fontSize: 20),),
            Row(
              mainAxisAlignment: MainAxisAlignment.center,
              children: const [
                FaIcon(FontAwesomeIcons.amazon,color: Colors.deepOrange,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.facebook,color: Colors.blue,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.github,color: Colors.black,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.twitter,color: Colors.blueAccent,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.aws,color: Colors.deepOrange,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.pinterest,color: Colors.red,size: 35,),
                SizedBox(width: 15,),
                FaIcon(FontAwesomeIcons.wordpress,color: Colors.deepPurple,size: 35,),
              ],
            ),
          ],
        ),
      ),
    );

Hope you enjoy flutter new things!

By Ami

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Today, I would like to share about differences between PHP and Nodejs for backend. Obviously, They have their own properties on particular aspects. The following are their comparisons.

Concurrency: Synchronous vs. Asynchronous

PHP is synchronous by nature, so it executes code line by line. When PHP code is executed, it waits for the current line to finish execution before it moves to the next line, and thus, it blocks the request.

Node.js is asynchronous by nature, so code doesn’t wait for I/O operations to complete their execution. For handling slow operations like I/O or remote data fetching, Node uses callbacks, promises, or JavaScript’s built-in and keywords. This makes Node.js pretty fast and makes it easy for a Node server to handle a high number of connections.

Runtime Environment: Zend Engine vs. V8 JavaScript Engine

PHP runs on the Zend engine, which is an open-source scripting engine which interprets the PHP code.

Node.js is an open-source, cross-platform, back-end JavaScript runtime environment that runs on Google’s V8 JavaScript engine.

Package Manager: Composer vs. NPM

Package management is one of the gray areas in PHP and has been a topic for debate over the years. There has never been a standard package manager which PHP developers could use to install reusable PHP libraries and components. PEAR was a widely-used package manager for PHP, but can now be thought to be deprecated. However, with initiatives like PHP-FIG and Composer, the PHP community has finally got a reliable system. Composer can be considered the standard package manager for PHP.

On the other hand, Node.js already provides NPM (Node Package Manager), a package management system. It is easy to use NPM to manage Node packages in your application. In fact, NPM has become the de facto standard for sharing reusable JavaScript components.

Performance

Node.js is asynchronous by nature, and thus, it has superior performance on tasks with a lot of connections or a lot of time-consuming I/O or network operations. However, it’s important to note that Node.js is single-threaded by default, so a CPU-intensive operation in one request will block all connections to the server until it is complete.

By Asahi

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